| | --- |
| | library_name: transformers |
| | base_model: microsoft/CodeGPT-small-java |
| | tags: |
| | - generated_from_trainer |
| | metrics: |
| | - accuracy |
| | model-index: |
| | - name: microsoft_CodeGPT-small-java_0_ft_clm |
| | results: [] |
| | --- |
| | |
| | <!-- This model card has been generated automatically according to the information the Trainer had access to. You |
| | should probably proofread and complete it, then remove this comment. --> |
| |
|
| | # microsoft_CodeGPT-small-java_0_ft_clm |
| |
|
| | This model is a fine-tuned version of [microsoft/CodeGPT-small-java](https://huggingface.co/microsoft/CodeGPT-small-java) on an unknown dataset. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 1.1672 |
| | - Accuracy: 0.7708 |
| |
|
| | ## Model description |
| |
|
| | More information needed |
| |
|
| | ## Intended uses & limitations |
| |
|
| | More information needed |
| |
|
| | ## Training and evaluation data |
| |
|
| | More information needed |
| |
|
| | ## Training procedure |
| |
|
| | ### Training hyperparameters |
| |
|
| | The following hyperparameters were used during training: |
| | - learning_rate: 8e-05 |
| | - train_batch_size: 4 |
| | - eval_batch_size: 12 |
| | - seed: 42 |
| | - distributed_type: multi-GPU |
| | - num_devices: 2 |
| | - gradient_accumulation_steps: 4 |
| | - total_train_batch_size: 32 |
| | - total_eval_batch_size: 24 |
| | - optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
| | - lr_scheduler_type: cosine |
| | - lr_scheduler_warmup_ratio: 0.02 |
| | - num_epochs: 5 |
| | |
| | ### Training results |
| | |
| | | Training Loss | Epoch | Step | Validation Loss | Accuracy | |
| | |:-------------:|:------:|:----:|:---------------:|:--------:| |
| | | 0.8842 | 0.7788 | 500 | 1.1934 | 0.7688 | |
| | | 0.7557 | 1.5576 | 1000 | 1.1676 | 0.7693 | |
| | | 0.7033 | 2.3364 | 1500 | 1.1631 | 0.7705 | |
| | | 0.6624 | 3.1153 | 2000 | 1.1650 | 0.7707 | |
| | | 0.6414 | 3.8941 | 2500 | 1.1646 | 0.7710 | |
| | | 0.6187 | 4.6729 | 3000 | 1.1672 | 0.7708 | |
| | |
| | |
| | ### Framework versions |
| | |
| | - Transformers 4.53.0 |
| | - Pytorch 2.7.1+cu126 |
| | - Datasets 3.6.0 |
| | - Tokenizers 0.21.2 |
| | |
